scholarly journals Single-Camera-Based Bridge Structural Displacement Measurement with Traffic Counting

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4517
Author(s):  
Zulhaj Aliansyah ◽  
Kohei Shimasaki ◽  
Taku Senoo ◽  
Idaku Ishii ◽  
Shuji Umemoto
Keyword(s):  
Motion Capture ◽  
Displacement Measurement ◽  
Single Camera ◽  
Motion Capture System ◽  
Side View ◽  
Civil Structures ◽  
Counting System ◽  
Front View ◽  
Dynamic Displacement ◽  
Measured Displacement

Vision-based structural displacement methods allow convenient monitoring of civil structures such as bridges, though they are often limited due to the small number of measurement points, constrained spatial resolution, and inability to identify the acting forces of the measured displacement. To increase the number of measurement points in vision-based bridge displacement measurement, this study introduces a front-view tandem marker motion capture system with side-view traffic counting to identify the force-inducing passing vehicles on the bridge’s deck. The proposed system was able to measure structural displacement at submillimeter resolution on eight measurement points at once at a distance of 40.8–64.2 m from a front-view camera. The traffic counting system with a side-view camera recorded the passing vehicles from two opposing lanes. We conducted a 35-min experiment for a 25 m-span steel road bridge with hundreds of cars passing over it and confirmed dynamic displacement distributions with amplitudes of several millimeters when large vehicles passed.

Dynamic Displacement Estimation from Acceleration Measurements Using a Wireless Smart Sensor

2013 ◽  
Vol 558 ◽  
pp. 227-234
Author(s):  
Jong Woong Park ◽  
Sung Han Sim ◽  
Hyung Jo Jung ◽  
Billie F. Spencer
Keyword(s):  
Large Scale ◽  
Low Frequency ◽  
Estimation Algorithm ◽  
Reference Points ◽  
Displacement Measurement ◽  
Frequency Drift ◽  
Smart Sensor ◽  
Civil Structures ◽  
Dynamic Displacement ◽  
Displacement Estimation

A displacement measurement provides useful information for structural health monitoring (SHM) as it is directly related to stiffness of the structure. Most existing methods of direct measurement such as the Laser Doppler Vibrometer (LDV) and the Liner Variable Differential Transformer (LVDT) are known to have accurate performance but have difficulties particularly in the use of large-scale civil structures as the methods rely on fixed reference points. Alternatively, indirect methods have been developed and widely used methods are Global Positioning System (GPS), vision-based displacement measurement system and displacement estimation from acceleration record. Among the indirect method, the use of accelerometer provides simple and economical in term of both hardware installation and operation. The major problem using acceleration based displacement estimation is low frequency drift caused by double integration. Recently, dynamic displacement estimation algorithm that addresses low-frequency drift problem has been developed. This study utilizes Wireless Smart Sensor (WSN) for estimating dynamic displacement from acceleration measurement in combination with the recently developed displacement estimation algorithm. Integrated into WSN that are low-cost, wireless, compatible with accelerometers, and capable of onboard computation, the displacement can be measured without limit of location on large-scale civil structures. Thus, this approach has the significant potential to impact many applications that require displacement measurements. With the displacement estimation algorithm embedded, the WSN performs in-network data processing to estimate displacements at each distributed sensor location wirelessly using only measured acceleration data. To experimentally validate the performance of displacement estimation using WSN for the use in structures with multiple-degree of freedom, the random vibration test is conducted on the three-story shear building model. The estimated displacement is compared with the reference displacements measured from the laser displacement sensor and the result shows good agreement.

The measurement of in vivo joint angles during a squat using a single camera markerless motion capture system as compared to a marker based system

2015 ◽  
Vol 41 (2) ◽  
pp. 694-698 ◽  
Author(s):  
Anne Schmitz ◽  
Mao Ye ◽  
Grant Boggess ◽  
Robert Shapiro ◽  
Ruigang Yang ◽  
...  
Keyword(s):  
Motion Capture ◽  
Single Camera ◽  
Motion Capture System ◽  
Joint Angles ◽  
Markerless Motion Capture

Gender differences in the Achilles tendon load during the fencing lunge

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Jonathan Kenneth Sinclair ◽  
Lindsay Bottoms
Keyword(s):  
Gender Differences ◽  
Achilles Tendon ◽  
Motion Capture ◽  
Tendon Injury ◽  
Force Platform ◽  
Motion Capture System ◽  
3D Motion ◽  
Loading Rates ◽  
Tendon Pathology ◽  
3D Motion Capture

AbstractRecent epidemiological analyses in fencing have shown that injuries and pain linked specifically to fencing training/competition were evident in 92.8% of fencers. Specifically the prevalence of Achilles tendon pathology has increased substantially in recent years, and males have been identified as being at greater risk of Achilles tendon injury compared to their female counterparts. This study aimed to examine gender differences in Achilles tendon loading during the fencing lunge.Achilles tendon load was obtained from eight male and eight female club level epee fencers using a 3D motion capture system and force platform information as they completed simulated lunges. Independent t-tests were performed on the data to determine whether differences existed.The results show that males were associated with significantly greater Achilles tendon loading rates in comparison to females.This suggests that male fencers may be at greater risk from Achilles tendon pathology as a function of fencing training/ competition.

Magnetic motion capture system using LC resonant magnetic marker composed of Ni–Zn ferrite core

2006 ◽  
Vol 99 (8) ◽  
pp. 08B312 ◽  
Author(s):  
S. Hashi ◽  
M. Toyoda ◽  
M. Ohya ◽  
Y. Okazaki ◽  
S. Yabukami ◽  
...  
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Ferrite Core ◽  
Zn Ferrite ◽  
Magnetic Marker

scholarly journals Modeling and evaluating beat gestures for social robots

2021 ◽  
Author(s):  
Unai Zabala ◽  
Igor Rodriguez ◽  
José María Martínez-Otzeta ◽  
Elena Lazkano
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Desirable Feature ◽  
Quantitative Results ◽  
Path Lengths ◽  
End Effectors ◽  
The One ◽  
Made In

AbstractNatural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemented by the Fréchet Gesture Distance (FGD) that aims to measure the fidelity of the generated gestures with respect to the provided ones. Results show that the described system is able to learn natural gestures just by observation and improves the one developed with a simpler motion capture system. The quantitative results are sustained by questionnaire based human evaluation.

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